The term “machine learning” refers to the algorithms that give the computers the ability to learn and to make predictions from data rather than follow a strict a program. Machine learning is divided into three types: supervised, unsupervised and reinforced.

Supervised

This takes place when the computer is presented with example inputs and desired outputs and must learn a general rule that will map input to output – for example, learning how to predict house prices based on size, area, number of bedrooms and so on.

Unsupervised

This consists of giving a computer no labels on the data you input. The computer must then search for patterns by itself and group the data accordingly. An example might be grouping news items of similar interest on a news website.

Reinforcement

This is where the computer learns to perform a task – such as driving a car or playing a game – by repeatedly interacting with its environment.

Search engines are an everyday example of machine learning. We need to have some understanding of search engines if our SEO is to be of benefit. Search engines are already very sophisticated. They consider a huge number of factors in order to rank web pages. Companies such as Dublin SEO agency http://www.rycomarketing.co.uk/search-engine-optimisation-seo.html have to be aware of this when they provide content.

They are also increasingly sophisticated in terms of the data they detect. Keywords are a good example. Keyword-stuffing no longer works, because search engines can detect it, identify it and discount or penalise it. Search engines can now look for synonyms, for relevant content and for phrases. This means that you have to provide quality content. You can find out more here: https://moz.com/blog/machine-learning-revolution.

As machine learning develops, search engines will define their own metrics: put simply, they will tell themselves what to look for. If they are looking for websites that satisfy searchers, they will begin to define which factors they should search for, which may be subsequent search activity or the length of time spent on a page.